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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Utilization of model-agnostic explainable artificial intelligence frameworks in oncology: a narrative review
Colton Ladbury, Reza Zarinshenas, Hemal Semwal, et al.
Translational Cancer Research (2022) Vol. 11, Iss. 10, pp. 3853-3868
Open Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Integration of artificial intelligence in lung cancer: Rise of the machine
Colton Ladbury, Arya Amini, Ameish Govindarajan, et al.
Cell Reports Medicine (2023) Vol. 4, Iss. 2, pp. 100933-100933
Open Access | Times Cited: 42
A critical moment in machine learning in medicine: on reproducible and interpretable learning
Olga Ciobanu-Caraus, Anatol Aicher, Julius M. Kernbach, et al.
Acta Neurochirurgica (2024) Vol. 166, Iss. 1
Open Access | Times Cited: 12
The Promise and Perils of Artificial Intelligence in Health Professions Education Practice and Scholarship
Gustavo A. Patiño, Jonathan M. Amiel, Megan E. L. Brown, et al.
Academic Medicine (2024) Vol. 99, Iss. 5, pp. 477-481
Open Access | Times Cited: 11
From pixels to prognosis: unveiling radiomics models with SHAP and LIME for enhanced interpretability
S. Raptis, Christos Ilioudis, Kiriaki Theodorou
Biomedical Physics & Engineering Express (2024) Vol. 10, Iss. 3, pp. 035016-035016
Open Access | Times Cited: 10
AI‐Enhanced Detection of Clinically Relevant Structural and Functional Anomalies in MRI: Traversing the Landscape of Conventional to Explainable Approaches
Pegah Khosravi, Saber Mohammadi, Fatemeh Zahiri, et al.
Journal of Magnetic Resonance Imaging (2024)
Closed Access | Times Cited: 9
A review of mechanistic learning in mathematical oncology
John Metzcar, Catherine R. Jutzeler, Paul Macklin, et al.
Frontiers in Immunology (2024) Vol. 15
Open Access | Times Cited: 9
Multi-Class Brain Tumor Grades Classification Using a Deep Learning-Based Majority Voting Algorithm and Its Validation Using Explainable-AI
Gopal S. Tandel, Ashish Tiwari, O. G. Kakde
Deleted Journal (2025)
Closed Access
Using XBGoost, an interpretable machine learning model, for diagnosing prostate cancer in patients with PSA < 20 ng/ml based on the PSAMR indicator
Dengke Li, Baoyuan Chang, Qunlian Huang
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis
Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin, et al.
Advanced Intelligent Systems (2025)
Open Access
The data scientist as a mainstay of the tumor board: global implications and opportunities for the global south
Myles Joshua Toledo Tan, Daniel Andrew Lichlyter, Nicholle Mae Amor Maravilla, et al.
Frontiers in Digital Health (2025) Vol. 7
Open Access
Artificial Intelligence-Based Methods for Drug Repurposing and Development in Cancer
Sara Herráiz-Gil, Elisa Nygren-Jiménez, Diana N. Acosta-Alonso, et al.
Applied Sciences (2025) Vol. 15, Iss. 5, pp. 2798-2798
Open Access
Opportunities for Artificial Intelligence in Oncology: From the Lens of Clinicians and Patients
Krunal Pandav, Sahar Almahfouz Nasser, Kristen H. Kimball, et al.
JCO Oncology Practice (2025)
Closed Access
Explainable Artificial Intelligence (XAI) in healthcare: Interpretable Models for Clinical Decision Support
Nitin Rane, Saurabh Choudhary, Jayesh Rane
SSRN Electronic Journal (2023)
Closed Access | Times Cited: 12
Artificial intelligence in cardiac surgery: A systematic review
Ralf Martz Sulague, Francis Joshua Beloy, Jillian Reeze Medina, et al.
World Journal of Surgery (2024) Vol. 48, Iss. 9, pp. 2073-2089
Open Access | Times Cited: 4
Deep learning algorithms for melanoma detection using dermoscopic imaging: A systematic review and meta-analysis
Zichen Ye, Daqian Zhang, Yuankai Zhao, et al.
Artificial Intelligence in Medicine (2024) Vol. 155, pp. 102934-102934
Closed Access | Times Cited: 4
Artificial intelligence and allied subsets in early detection and preclusion of gynecological cancers
Pankaj Garg, Atish Mohanty, Sravani Ramisetty, et al.
Biochimica et Biophysica Acta (BBA) - Reviews on Cancer (2023) Vol. 1878, Iss. 6, pp. 189026-189026
Open Access | Times Cited: 9
A deep learning‐based interpretable decision tool for predicting high risk of chemotherapy‐induced nausea and vomiting in cancer patients prescribed highly emetogenic chemotherapy
Jingyue Zhang, Xudong Cui, Chong Yang, et al.
Cancer Medicine (2023) Vol. 12, Iss. 17, pp. 18306-18316
Open Access | Times Cited: 8
Explainable Soft Attentive EfficientNet for breast cancer classification in histopathological images
Jyothi Peta, Srinivas Koppu
Biomedical Signal Processing and Control (2023) Vol. 90, pp. 105828-105828
Closed Access | Times Cited: 8
Insights from Explainable Artificial Intelligence of Pollution and Socioeconomic Influences for Respiratory Cancer Mortality in Italy
Donato Romano, Pierfrancesco Novielli, Domenico Diacono, et al.
Journal of Personalized Medicine (2024) Vol. 14, Iss. 4, pp. 430-430
Open Access | Times Cited: 2
Predicting axillary lymph node metastasis in breast cancer patients: A radiomics-based multicenter approach with interpretability analysis
Haohuan Li, Minping Hong, Xinhua Li, et al.
European Journal of Radiology (2024) Vol. 176, pp. 111522-111522
Closed Access | Times Cited: 2
Cherry on Top or Real Need? A Review of Explainable Machine Learning in Kidney Transplantation
Alvaro Assis de Souza, Andrew Stubbs, Dennis A. Hesselink, et al.
Transplantation (2024) Vol. 109, Iss. 1, pp. 123-132
Closed Access | Times Cited: 2
Predicting progression-free survival in patients with epithelial ovarian cancer using an interpretable random forest model
Lian Jian, Xiaoyan Chen, Pingsheng Hu, et al.
Heliyon (2024) Vol. 10, Iss. 15, pp. e35344-e35344
Open Access | Times Cited: 2
Assessment of brain cancer atlas maps with multimodal imaging features
Enrico Capobianco, Marco Dominietto
Journal of Translational Medicine (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 5
SurvIAE: Survival prediction with Interpretable Autoencoders from Diffuse Large B-Cells Lymphoma gene expression data
Gian Maria Zaccaria, Nicola Altini, Giuseppe Mezzolla, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 244, pp. 107966-107966
Open Access | Times Cited: 5
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